Unlock Insights From Business Documents With Revv’s Metalens, a Machine Learning Based Document Analyzer

Businesses run on documents as documents help build connections. They cement relationships and enable trust and transparency between stakeholders. Documents bring certainty, continuity, and clarity. When it comes to reviewing documents, most intelligence platforms perceive documents for their language content.

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A business document is not just written text, it’s a record of information and data – from simple entities such as names or addresses to more nuanced ones such as notice period or renewal dates – this information is required to optimize workflows and processes. Revv recently added Metalens, an intelligent document analyzer that breaks this barrier and applies artificial intelligence to extract data and intent from business documents to scale up business processes.

Metalens allows users to extract relevant information and identify potential discussion points from any document (pdf or Docx) within Revv. This extracted data can be reused to set up workflows, feed downstream business apps with relevant information, and optimize business processes. Think itinerary processing, financial compliance, auditing, renewal follow-up, invoice processing, and so on, all identified and automated. The feature improves process automation, which is otherwise riddled with copy-pasting errors and other manual data entry bottlenecks.

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With Metalens, users can –

• Extract all the important entities (in one document and replicate the system for all other documents)
• Fill up a form using datasets (also known as metadata in the product) or use this data to set up workflows
• Automatically tag and identify the potential discussion points of a document
• Create new documents using the same saved datasets (metadata)
• Create business-specific dashboards to track all relevant information
• Unearth the real intent of the clauses

Revv’s new Metalens feature gives its users the speed and flexibility to generate meaningful insights and accelerate business outcomes by putting machine learning front and center. It quickens the review process and makes negotiation smoother. It brings transparency that helps reduce errors and lets users save time and effort.

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